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Consider the following unequal error protection scenario. One special message, dubbed the “red alert” message, is required to have an extremely small probability of missed detection. The remainder of the messages must keep their average probability of error and probability of false alarm below a certain threshold. The goal then is to design a codebook that maximizes the error exponent of the red alert message while ensuring that the average probability of error and probability of false alarm go to zero as the blocklength goes to infinity. This red alert exponent has previously been characterized for discrete memoryless channels. This paper completely characterizes the optimal red alert exponent for additive white Gaussian noise channels with block power constraints. [ABSTRACT FROM PUBLISHER]

We introduce in this paper the concept of a correctable error set and a fixed initialization decoding, by noticing that the sum-product decoder with a given iteration number only depends on the initialized probability of error, for a BSC. Although this value has been conventionally selected as the BSC crossover probability, we show that other selections can provide better performance or faster convergence. We also prove that for any fixed initialization (i.e., any given correctable error set), the word-error-rate can be represented as a polynomial of the BSC crossover probability. This suggests that the word-error-rate can be analytically derived from the knowledge of the correctable error set. [ABSTRACT FROM AUTHOR]

The use of open-loop coding can be easily extended to a closed-loop concatenated code if the transmitter has access to feedback. This can be done by introducing a feedback transmission scheme as an inner code. In this paper, this process is investigated for the case when a linear feedback scheme is implemented as an inner code and, in particular, over an additive white Gaussian noise (AWGN) channel with noisy feedback. To begin, we look to derive an optimal linear feedback scheme by optimizing over the received signal-to-noise ratio (SNR). From this optimization, a linear feedback scheme is produced that is asymptotically optimal in the sense of blocklength-normalized SNR; it is then compared to other well-known schemes. Then, the linear feedback scheme is implemented as an inner code to a concatenated code over the AWGN channel with noisy feedback. This code shows improvements not only in error exponent bounds, but also in bit error rate (BER) and frame error rate (FER). It is also shown that if the concatenated code has total blocklength L and the inner code has blocklength, N, the inner code blocklength should scale as N = O\left(C\over R\right), where C is the capacity of the channel and R is the rate of the concatenated code. Simulations with low-density parity-check (LDPC) and turbo codes are provided to display practical applications and their error rate benefits. [ABSTRACT FROM AUTHOR]

The error-pattern correcting code (EPCC) is a code designed to correct frequently observed error cluster patterns of the intersymbol interference (ISI) channel. This paper focuses on developing theoretical understanding of the performance of serial concatenation of the EPCC with an outer recursive systematic convolutional code (RSCC) in ISI channel environments. To analyze the performance of this EPCC-RSCC concatenation, an upper union bound on the maximum-likelihood (ML) bit-error rate (BER), averaged over all possible interleavers, is derived which offers crucial insights into the error floor behavior of the matching turbo decoder. The ML bound is also used to compare the performance of EPCC-RSCC to that of a stand-alone RSCC in serial concatenation to precoded and nonprecoded ISI channels. This comparison shows that by targeting the low Hamming-weight interleaved errors of the RSCC, which result in low Euclidean distance error events in the channel detector, EPCC-RSCC exhibits a much lower BER floor compared to conventional schemes, especially for high rate applications and short interleaver lengths. The error rate performance of an iterative suboptimal turbo equalizer (TE), called TE-EPCC, is also demonstrated to converge close to the ML bound at high SNR. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of coding for the half-duplex nonorthogonal amplify-and-forward (NAF) cooperative channel where the transmitter to relay and the interrelay links are highly reliable. We derive bounds on the diversity order of the NAF protocol that are achieved by a distributed space-time bit-interleaved coded modulation (D-ST-BICM) scheme under iterative APP detection and decoding. These bounds lead to the design of space-time precoders that ensure maximum diversity order and high coding gains. The word error rate performance of D-STBICM are also compared to outage probability limits. [ABSTRACT FROM AUTHOR]

Tardos has proposed a randomized fingerprinting code that is provably secure against collusion attacks. We revisit his scheme and show that it has significantly better performance than suggested in the original paper. First, we introduce variables in place of Tardos' hard-coded constants and we allow for an independent choice of the desired false positive (FP) and false negative (FN) error rates. Following through Tardos' proofs with these modifications, we show that the code length can be reduced by more than a factor of two in typical content distribution applications where high FN rates can be tolerated. Second, we study the statistical properties of the code. Under some reasonable assumptions, the accusation sums can be regarded as Gaussian-distributed stochastic variables. In this approximation, the desired error rates are achieved by a code length twice shorter than in the first approach. Overall, typical FP and FN error rates may be achieved with a code length approximately five times shorter than in the original construction. [ABSTRACT FROM AUTHOR]